From 0b1bfaffcd92df72a9d69ebf26319e5e78c98212 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 16 Jan 2026 01:40:33 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 unsloth/models/vision.py | 12 +++---------
 1 file changed, 3 insertions(+), 9 deletions(-)

diff --git a/unsloth/models/vision.py b/unsloth/models/vision.py
index 48f97d49d7..f648199e3f 100644
--- a/unsloth/models/vision.py
+++ b/unsloth/models/vision.py
@@ -296,9 +296,7 @@ def unsloth_base_fast_generate(
     # Track metrics if enabled
     collector = None
     request_id = None
-    prompt_tokens_per_sequence = (
-        input_ids.shape[-1] if input_ids is not None else 0
-    )
+    prompt_tokens_per_sequence = input_ids.shape[-1] if input_ids is not None else 0
     prompt_batch_size = input_ids.shape[0] if input_ids.dim() > 1 else 1
     num_prompt_tokens = prompt_tokens_per_sequence * prompt_batch_size
     max_tokens = kwargs.get("max_new_tokens") or kwargs.get("max_length")
@@ -359,9 +357,7 @@ def unsloth_base_fast_generate(
                 # Handle ModelOutput when return_dict_in_generate=True
                 sequences = output["sequences"]
                 if isinstance(sequences, torch.Tensor):
-                    output_batch_size = (
-                        sequences.shape[0] if sequences.dim() > 1 else 1
-                    )
+                    output_batch_size = sequences.shape[0] if sequences.dim() > 1 else 1
                     if output_batch_size != prompt_batch_size:
                         effective_prompt_tokens = (
                             prompt_tokens_per_sequence * output_batch_size
@@ -377,9 +373,7 @@ def unsloth_base_fast_generate(
                 # Handle ModelOutput object directly
                 sequences = output.sequences
                 if isinstance(sequences, torch.Tensor):
-                    output_batch_size = (
-                        sequences.shape[0] if sequences.dim() > 1 else 1
-                    )
+                    output_batch_size = sequences.shape[0] if sequences.dim() > 1 else 1
                     if output_batch_size != prompt_batch_size:
                         effective_prompt_tokens = (
                             prompt_tokens_per_sequence * output_batch_size